Digitizing the Experiences of Migrant Labour in Qatar

This study used participatory oral history and digital archiving to explore two interrelated questions: How do Indo-Caribbean women and gender-expansive people across generations experience processes of storytelling? What are the challenges and possibilities of oral history and digital archiving for constructing alternative histories and genealogies of resistance? In the first phase of the study, twelve Indo-Caribbean women and gender-expansive people across generations participated in an oral history workshop where they were introduced to oral history methods, co-created an interview guide, conducted oral history interviews of one another, and engaged in collective reflection about processes of storytelling. In the second phase, four co-authors of a community-owned digital archive participated in semi-structured interviews about their work to craft new narratives of diasporic resistance rooted in the everyday stories of Indo-Caribbean women and gender-expansive people. In this paper, I analyze how Indo-Caribbean women and gender-expansive people practice resistance by breaking silences in their communities around gender-based oppression, shift norms through producing analyses of their own stories, and reshape community narratives. Furthermore, I explore how oral history participants and co-authors of a digital archive understand the risks associated with sharing stories, raising the ethical dilemmas associated with conceptualizing storytelling as purely liberatory.

The digital hospital information technology in radiology

Trigger-action platforms (TAPs) enable users without programming experience to personalize the behavior of Internet of Things applications and services through IF-THEN rules. Unfortunately, the arbitrary connection of smart devices and online services, even with simple rules, such as “IF the entrance Netatmo Wheather Station detects a temperature above 30 \({}^{\circ}C\) ( \(86^{\circ}F\) ) THEN open the shutters in the living room,” might expose users to potential security and privacy risks (e.g., the execution of the previous rule might provide an easy entry point for thieves, especially during the summer vacation period). The goal of our research is to make the users capable of understanding and mitigating the threats and risks associated with the execution of IF-THEN rules. To this end, we define a new challenging task, namely generating post hoc justifications of privacy and security risks associated with automation rules, and propose a novel natural language generation strategy based on hybrid prompt learning producing justifications in the form of real-life threat scenarios. The proposed strategy allows for prompt customization with task-specific information, providing contextual details enabling to grasp the nuances and subtleties of the domain language, resulting in more coherent justifications. The experiments conducted on the if-this-then-that (IFTTT) platform show that our method produces effective justifications, improving the explainability of discrete and hybrid prompting methods up to 27% in BLEURT score. The code of the software is publicly available on GitHub 1 .

The purpose of current research is to find the impact of perceived security and privacy risks on online shopping intentions of consumers in the education sector. The security and privacy risks being antecedents of online purchase intentions of customers examined with the help of quantitative research methodology. The quantitative research design followed survey method to collect data using convenience sampling. The questionnaires-based survey conducted to obtain responses and final analysis conducted on 350 duly filled questionnaires. Smart PLS 4.0 software utilized in which bootstrapping technique used for statistical estimations. The data found to be reliable using Cronbach’s alpha and composite reliability. All the items of variables found to be valid using cross loading and outer loading. The results indicate that perceived privacy risk negatively impacts online shopping intentions of consumers, while perceived security risk has no impact on online shopping intentions of consumers. Future research could explore the moderating effect of gender between relationships of perceived privacy risk, security risk and online purchase intentions of consumers. The study can utilize nonstudent samples in future for generalizability of research.

Problem setting. There is evidence that Political power plays a crucial role in regulating social processes. But it is also a difficult concept to understand and define. That`s why this phenomenon has been studied by many researchers using different methods and absolutely different scientific approaches, what has made it an ambigious term. It causes an actuality of synthesizing the most significant innovative concepts into unite theoretical background.
 Resent research and publication analysis. Previous research has established that Political power is related to Power of law. A number of cross-sectional studies suggest an association between Political power and Public governance, State Power. The issue has been a controversial and much disputed subject within the multidisciplinary field of sociological, culturelogical, psychological and even linguistical researches. As a result, this concept has recently been challenged by postmodernist`s studies demonstrating its hidden features. We should notice a big number of scholars, from M. Faucault and P. Bourdieu to S. Lukes and K. Dowding, whose developments in the field of Cratology have led to a renewed interest in political power.
 Paper objective. The purpose of this investigation is to explore the innovative approaches to political power understanding and to give own definition of this phenomenon.
 Paper main body. The methodological approach taken in this study is a mixed methodology based on qualitative and quantative, theoretical and empirical studies. The overall structure of the study takes the form of two conditional parts. The first part of this paper examines the innovative approaches to general power understanding. In the section we are proving that power is based on information. The second part also begins by laying out the theoretical dimensions of the research, and looks what is political power at postmodernist`s context. In summary, information is seemed to be the most efficient power resource, because it touches each part of people existence.
 Conclusions of the research. So, we can confirm that political power is perceived rather as communicative, mental concept than a part of state`s institution system. In other words, now it is believed that modern power as kind of social influence is appearing from every part of social life due to its cognitive nature, but at the same time it is almost disappearing as traditional part of government structure. The result of the analysis is also proclaimed by the author's approach to the rationalization of “political power”: “classical” (power and political power are the same), “institutional” (based on the law and the state form of political power) and “functional” (based on the information power that is aimed to political processes. The next result of the article is our political power clarifying. According to the R. Dahl’s definition and the V. Ledyaev’s classification we define political power as a “A`s possibility to construct B`s “picture of the world”. So, this study seems to be relevant. In conclusion I’d like to say that this topic is perceived as inexhaustible and that theme is still so actual for further multidisciplinary researches.

The Archival Science Study Program, run by the Vocational College at Universitas Gadjah Mada, has produced numerous oral history archives since 1997 and has contributed diverse themes through the Oral History Program course in practical subjects. These oral history archives can be used by the public, through information technology, to facilitate knowledge transfer and as oral evidence using the ARISAN (Arsip Sejarah Lisan) mobile application. This study aims to describe the implementation of the oral history archives dissemination program, as one of the models used for oral evidence, as well as for recording the oral history published in the community.

Federated Learning (FL) is a decentralised approach to training statistical models, where training is performed across multiple clients, producing one global model. Since the training data remains with each local client and is not shared or exchanged with other clients the use of FL may reduce privacy and security risks (compared to methods where multiple data sources are pooled) and can also address data access and heterogeneity problems. Synthetic data is artificially generated data that has the same structure and statistical properties as the original but that does not contain any of the original data records, therefore minimising disclosure risk. Using FL to produce synthetic data (which we refer to as "federated synthesis") has the potential to combine data from multiple clients without compromising privacy, allowing access to data that may otherwise be inaccessible in its raw format. The objective was to review current research and practices for using FL to generate synthetic data and determine the extent to which research has been undertaken, the methods and evaluation practices used, and any research gaps. A scoping review was conducted to systematically map and describe the published literature on the use of FL to generate synthetic data. Relevant studies were identified through online databases and the findings are described, grouped, and summarised. Information extracted included article characteristics, documenting the type of data that is synthesised, the model architecture and the methods (if any) used to evaluate utility and privacy risk. A total of 69 articles were included in the scoping review; all were published between 2018 and 2023 with two thirds (46) in 2022. 30% (21) were focussed on synthetic data generation as the main model output (with 6 of these generating tabular data), whereas 59% (41) focussed on data augmentation. Of the 21 performing federated synthesis, all used deep learning methods (predominantly Generative Adversarial Networks) to generate the synthetic data. Federated synthesis is in its early days but shows promise as a method that can construct a global synthetic dataset without sharing any of the local client data. As a field in its infancy there are areas to explore in terms of the privacy risk associated with the various methods proposed, and more generally in how we measure those risks.

This study examines the ethical and privacy challenges of integrating generative artificial intelligence (AI) into electronic health record (EHR) systems, focusing on Tanzania's healthcare context. It critically analyses the extent to which Tanzania's Policy Framework for Artificial Intelligence in the Health Sector (2022) addresses these challenges and proposes regulatory and practical safeguards for responsible generative AI deployment. A systematic scoping review was conducted using PubMed, IEEE Xplore, Scopus and Google Scholar to identify relevant studies published between 2014 and 2024. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines informed the search and selection process. Fourteen studies met the inclusion criteria and were thematically analysed to identify key ethical and privacy concerns of generative AI in healthcare. Moreover, a policy analysis of Tanzania's AI framework was conducted to assess its alignment with global best practices and regulatory preparedness. The review identified six key ethical and privacy challenges associated with generative AI in EHR systems: data privacy and security risks, algorithmic bias and fairness concerns, transparency and accountability issues, consent and autonomy challenges, human oversight gaps and risks of data re-identification. The policy analysis revealed that while Tanzania's AI framework aligns with national health priorities and promotes capacity building and ethical governance, it lacks generative AI-specific guidelines, regulatory clarity and resource mobilisation strategies necessary for healthcare settings. Integrating generative AI into Tanzania's EHR systems presents transformative opportunities and significant ethical and privacy risks. Tanzania's policy framework should incorporate AI-specific ethical guidelines, operationalise regulatory mechanisms, foster stakeholder engagement through participatory co-design and strengthen infrastructural investments. These measures will promote ethical integrity, enhance patient trust and position Tanzania as a regional leader in responsible AI use in healthcare.

This article presents a case study about a recent collaboration between the Louie B. Nunn Center for Oral History at the University of Kentucky Libraries and a professor at the University of Kentucky to use the Oral History Metadata Synchronizer (OHMS)—an open source, free online application originally designed for enhancing archival access to oral history—as a pedagogical tool to elevate student engagement with oral history in the classroom. The authors—the oral history center director and creator of OHMS; a professor in the Department of Writing, Rhetoric, and Digital Studies (WRD); and an undergraduate WRD student assigned the task of using OHMS to index oral history—reflect on this collaboration from their own perspectives. This collaboration between the archive and the classroom at the University of Kentucky provides an innovative, experiential learning model for engaging undergraduate students in the critical thinking and research aspects of working with oral history, and the article reflects on the impact and potential for future applications of this model.

While computer-related failures are known to play a significant role in deaths and injuries involving medical devices reported to the U.S. Food and Drug Administration (FDA),1 there is no similar reporting system that meaningfully captures security-related failures in medical devices.Medical device software must satisfy system properties, including safety, security, reliability, resilience, and robustness, among others. This column focuses on the challenges to satisfying a security property for medical devices: post-market surveillance, integrity and availability, and regulation and standards.Medical devices depend on software for patient care ranging from radiation therapy planning to pharmaceutical compounding to automated diagnosis of disease with mobile medical apps. Meanwhile, the medical community has observed an uptick in reported security vulnerabilities in medical device software—raising doubts of cybersecurity preparedness. It should come as little surprise that security risks in medical devices "could lead to patient harm" as recently explained by the chief scientist at the FDA Center for Devices and Radiological Health.2 Device manufacturers and healthcare providers ought to more carefully and deliberately consider security hazards during the phases from design to use of medical devices.Between years 2006 and 2011, 5,294 recalls and approximately 1.2 million adverse events of medical devices were reported to the FDA's Manufacturer and User Facility Device Experience (MAUDE) database.1 Almost 23% of these recalls were due to computer-related failures, of which approximately 94% presented medium to high risk of severe health consequences (such as serious injury or death) to patients.1 For security incidents on medical devices, no systematic national reporting system exists.3 Yet, individual hospitals know of hundreds of security incidents on medical devices.2For instance, the FDA MAUDE does not capture adverse events such as lack of or impaired availability of function when malware infects a medical device's operating system. FDA's own disclaimer explains that the MAUDE database is qualitative rather than quantitative. MAUDE is incomplete with underreporting and reporting bias.Imagine the reaction of a clinician using a high-risk pregnancy monitor that begins to perform more slowly because of a Conficker infection. Would the clinician report a malware infection? Likely not. Admitting to playing a role in accidentally infecting a medical device-would likely lead to consequences ranging from disciplinary action to loss of reputation. Thus, the actual incidence of security failures leading to healthcare delivery failures may be significantly greater than the available statistics suggest. To have a better understanding of medical device security, the bad-news diode must be shorted. Reporting must be incentivized rather than penalized.If you watch television crime dramas, you may be duped into thinking that hacking of medical devices is the number-one risk for public health today. You would be wrong. The most pressing risks are much less sexy: the unavailability of patient care and the lack of health data integrity. Here, we highlight a few examples that illustrate the consequences of unavailability and lack of integrity.Interventional radiology suites and cardiac catheterization labs contain a number of computer systems to perform time-sensitive cardiac procedures, such as angioplasty, to open blocked arteries for improved outcomes in patients suffering acute heart attacks or strokes.According to The Wall Street Journal,2 a Department of Veterans Affairs (VA) catheterization laboratory in New Jersey was temporarily closed in January 2010. Malware had infected the computer systems. The consequence? Patients do not receive the safe and effective care they deserve when malware causes unavailability of care. The VA has experienced hundreds of malware infections in medical devices such as X-ray machines and lab equipment made by well-known, reputable companies.Conficker was detected on 104 devices at the James A. Haley Veterans Hospital in Tampa.2 The affected devices included an X-ray machine, mammography, and a gamma camera for nuclear medicine studies. Conficker is a relatively old piece of malware with well-known mitigation strategies. Why does old malware persist on medical devices?We observe that one of the cultural challenges to improved cybersecurity and t herefore safety and effectiveness is a lifecycle mismatch. For instance, operating system software with production lifecycles measured in months does not match well with a medical device having production lifecycles measured in years or decades. The equivalent of a transformer for impedance matching does not yet exist for safely connecting these different production cultures.Risks of depending on unsupported software has parallels to depending on a device where parts are no longer manufactured or repaired. Medical devices still rely on the original versions of Windows XP (circa 2001). In October 2012, the Beth Israel Deaconess Medical Center in Boston reported to the NIST Information Security and Privacy Advisory Board that the hospital depends on 664 Windows-based medical devices primarily because of supply chain issues. Of the 664 computers, 600 devices run the original version of Windows XP. There are no Service Pack 1 (SP1) machines, but there are 15 SP2 machines and 1 SP3 machine. One MRI machine still runs Windows 95. Security support for SP1, SP2, and SP3 ended on October 10, 2006, July 13, 2010, and April 14, 2014, respectively. In many cases, a medical device manufacturer does not provide an effective way for hospitals to upgrade to supported versions of operating systems. Today, healthcare providers are told to maintain a secure system from insecure devices.4A medical device infected with malware can stray from its expected behavior. For instance, malware can cause a device to slow down and miss critical interrupts. When this happened on a high-risk pregnancy monitor, healthcare professionals could no longer trust the integrity of the sensor readings and depended on backup methods.5Antivirus software can help mitigate certain cybersecurity risks, but they also introduce their own risks. On April 21, 2010, a third of the hospitals in Rhode Island were forced to "postpone elective surgeries and stop treating patients without traumas in emergency rooms" because an automated antivirus software update had accidentally misclassified a critical Windows DLL as malicious. The problem with antivirus software is that by definition, antivirus software is a postmarket afterthought to make up for design flaws in the device. Antivirus software does not remove the need to incorporate security into the early design of medical devices.According to the FDA mission statement, the agency holds responsibility for protecting public health by assuring the safety, efficacy, and security of medical devices. In June of this year, the FDA issued draft guidance on cybersecurity6 and gave examples of what FDA reviewers would expect to see during premarket review. The draft guidance intentionally does not prescribe any particular approach or technology but instead recommends that manufacturers consider cybersecurity starting at the concept phase of the medical device.The FDA recommends that manufacturers provide:Standards bodies are taking actions to improve medical device cybersecurity. For instance, the Association for the Advancement of Medical Instrumentation (AAMI) recently formed a working group on medical device security that includes engineers from manufacturing and regulators. AAMI has already released standards specific to network-related cybersecurity risks (ANSI/AAMI/IEC-80001). International harmonization of cybersecurity guidance is likely on the horizon, given that phrases such as "security patches" appear in proposals from the International Medical Device Regulators Forum.Modern healthcare delivery depends on medical device software to help patients lead more normal and healthy lives. Medical device security problems are real, but the focus on hacking goes only skin deep. Consequences of diminished integrity and availability caused by untargeted malware include the inability to deliver timely and effective patient care. By addressing security and privacy risks at the concept phase, medical devices can remain safe and effective despite the cybersecurity threats endemic to computing. Security of medical devices is more than just a potential problem on the horizon.This work was supported in part by NFS CNS-1331652 and HHS 90TR0003/01. Any opinions, findings, and conclusions expressed in this material are those of the authors and do not necessarily reflect the views of NSF or HHS.

The field of artificial intelligence (AI) has experienced remarkable progress in recent years, driven by the widespread adoption of open-source machine learning models in both research and industry. Considering the resource-intensive nature of training on vast datasets, many applications opt for models that have already been trained. Hence, a small number of key players undertake the responsibility of training and publicly releasing large pre-trained models, providing a crucial foundation for a wide range of applications. However, the adoption of these open-source models carries inherent privacy and security risks that are often overlooked. To provide a concrete example, an inconspicuous model may conceal hidden functionalities that, when triggered by specific input patterns, can manipulate the behavior of the system, such as instructing self-driving cars to ignore the presence of other vehicles. The implications of successful privacy and security attacks encompass a broad spectrum, ranging from relatively minor damage like service interruptions to highly alarming scenarios, including physical harm or the exposure of sensitive user data. In this work, we present a comprehensive overview of common privacy and security threats associated with the use of open-source models. By raising awareness of these dangers, we strive to promote the responsible and secure use of AI systems.

Digitised versions of archival fonds with micro or regional significance daily join mass digitisation projects of books and documents in the global digital space. For historians, the exponential expansion of searchable digital archival material has required the revision of traditional research methods. The digital age has also shifted disciplinary boundaries such as the distinction between historian and archivist. This article concerns a micro digitisation involving collaboration between historian and archivist, not in archive access as is usually the case, but in archive creation. The experience of this collaboration is generalisable to other micro-scale uploads of scanned material enabled by digital technologies. This article is a case study of this experience. It uses autoethnography to explore the practicalities and ethical processes of decision-making to create a new digital archive of wine history during the pilot stage of an Australian Research Council Industry Linkage Grant. The decision-making process that transformed a historian as traditional archive end-user to archive creator highlights the challenges for both professions in the decision to digitise, the implications for expenditure of public funds and questions of digitisation and environmental sustainability.

The online shopping process in Bandar Lampung is facilitating by mobile commerce online shopping. The factor of using online shopping mobile commerce has never been analyzed based on the public perception in Bandar Lampung. This research discusses using mobile-commerce online shopping using the UTAUT2 model with Perceived Risk manifestations, namely Security Risk and Privacy Risk. The mobile commerce applications analyzed were Shopee, Lazada, Tokopedia, Bukalapak, and Blibli. The purpose of this research was to determine the UTAUT2 variable with the manifestation of Perceived Risk, namely Security Risk and Privacy Risk, which affect the use of online shopping mobile commerce. The data analysis method used is Structural Equation Modeling (SEM) with Partial Least Square (PLS) approach. The total number of respondents obtained was 183 respondents. The data tested were 373 data. This research results from the factors that most influence the behavioral intention and use behavior of mobile commerce online shopping is a habit.

This text shows changes in the way oral history has been perceived in the last 10 years in Poland, what projects are being conducted at the moment and where research on this subject is going.
 Contemporary research in oral history has taken a few directions. First, this method is treated as a source prompted by historians and used in by them in research activity. Second, an interest taken in this method is manifested in methodological and historiographic reflection. The third group is research on archiving audio-visual documents. Another area of interest for oral history is widely understood education and popularization of this method. 
 In Poland there are a few serious institutions/centrers that focus their research and work methods on oral form of information, such as Narodowe Archiwum Cyfrowe (National Digital Archive) and Centrum Edukacji Obywatelskiej (Center for Civic Education). Widely available are internet sources such as „Uczyć się z historii” (“To Learn from History”) and „Świadkowie Historii” (“Witnesses to History”), which gather oral evidence from people all over Poland. The article discusses also activities of the KARTA Center from Wrocław, “Brama Grodzka – Teatr NN” (Grodzka Gate – NN Theatre) Center and Studio Historii Mówionej (Oral History Center) from Lublin. The Memory and Future Institute from Wrocław is a thriving institution as well. An analysis has also been made of initiatives taken by circles in Olsztyn, Łódź, and at the Auschwitz-Birke-nau Museum.
 In 2009 the first in Poland Oral History Society was founded (Towarzystwo Historii Mówionej). This was possible thanks to institutions that are growing and becoming more and more active, and also because of academics who take interest in this kind of research. Every year the Society organizes nationwide conferences. Also other academic centers and societies organize conferences and meetings devoted to the culture of memory and oral history.

The Internet-of-Things (IoT) ushers in a new age where the variety and amount of connected, smart devices present in the home is set to increase substantially. While these bring several advantages in terms of convenience and assisted living, security and privacy risks are also a concern. In this article, we consider this risk problem from the perspective of technology users in the smart home, and set out to provide a usable framework for modelling security and privacy risks. The novelty of this work is in its emphasis on supplying a simplified risk assessment approach, complete with typical smart home use cases, home devices, IoT threat and attack models, and potential security controls. The intention is for this framework and the supporting tool interface to be used by actual home users interested in understanding and managing the risks in their smart home environments.